Various methods for search and retrieval of information, such as by a search engine over the Internet, are known in the art. Such methods typically employ text-based searching. Text-based searching employs a search query that comprises one or more textual elements such as words or phrases. The textual elements are compared to an index or other data structure to identify webpages, documents, images, and the like that include matching or semantically similar textual content, metadata, file names, or other textual representations.
The known methods of text-based searching work relatively well for text-based documents, however they are difficult to apply to image files and data. In order to search image files via a text-based query the image file must be associated with one or more textual elements such as a title, file name, or other metadata or tags. Often a human judge is required to view and label each image separately. The search engines and algorithms employed for text based searching cannot search image files based on the content of the image and thus, are limited to identifying search result images based only on the data associated with the images.
Methods for content-based searching of images have been developed that utilize one or more analysis of the content of the images to identify visually similar images. These methods however, are laborious and may require a great deal of input from a user to characterize an image before a search can be performed. Further, such methods are inefficient and do not scale well to a large scale, wherein, for example, several billion images must be quickly searched to identify and provide search result images to a user.